<![CDATA[Discipline is a crucial aspect of education that plays a significant role in shaping students’ character and sense of responsibility. However, the manual discipline assessment process at SDIP Baitul Maal presents several issues, such as inaccurate data, limited analysis capabilities, and difficulty for teachers and parents to monitor students effectively. With the advancement of information technology, digital systems offer a potential solution to improve the efficiency and objectivity of the evaluation process. This study aims to design and develop a web-based application for assessing student discipline by implementing the K-Means Clustering method optimized with the Elbow method. The system is designed to cluster students based on numerical data such as attendance, tardiness, neatness, and rule violations, allowing for more accurate classification of discipline levels. The results show that the system successfully groups students into clusters automatically and provides informative visualizations of the outcomes. Additionally, the system facilitates real-time monitoring and evaluation by school staff and parents through a user-friendly interface. Therefore, the application of the K-Means Elbow method proves effective in supporting decision-making within the educational environment. This research is expected to contribute to the digital transformation of school management and enhance the quality of student character development.]]>
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